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Reduced probability of smoking cessation in men with
increasing number of job losses and partnership
breakdowns
Margit Kriegbaum, Anne Mette Larsen, Ulla Christensen, Rikke Lund, Merete
Osler
To cite this version:
Title: Reduced probability of smoking cessation in men with increasing number of job-losses and partnership breakdowns
Margit Kriegbaum MSca, Larsen, Anne Mette MDa, Ulla Christensen PhDa, Rikke Lund PhDa, Merete Osler DrMScab
Author affiliations:
a. Department of Public Health, University of Copenhagen, Denmark
b. Research Centre for Prevention and Health, Glostrup University Hospital, Denmark
Corresponding author:
M Kriegbaum
Institute of Public Health Øster Farimagsgade 5 1014 Copenhagen
E-mail [email protected] Tel: +45 35327143
Fax +45 35351181
Abstract
Background: Unemployment and partnership breakdowns are common stressful life events, but
their association with smoking cessation has been investigated in a few studies only. Objective: To investigate how history of employment and cohabitation affect the probability of smoking cessation and to study joint exposure to both. Methods: Birth-cohort study of smoking cessation of 6,232 Danish men born in 1953 with follow-up at age 51 (response rate 66.2 %). History of
unemployment and cohabitation was measured annually using register data. Information on smoking cessation was obtained by questionnaire. Results: Probability of smoking cessation decreased with number of job-losses (ranging from 1 OR 0.54 95% CI (0.46-0.64) to 3+ OR 0.41 95% CI (0.30-0.55)) and of broken partnerships (ranging from 1 OR 0.74 95% CI (0.63-0.85) to 3+ OR 0.50 95% CI (0.39-0.63)). Furthermore, smoking cessation was associated with the duration of the periods of unemployment (ranging from 1-5 years OR 0.75 95% CI (0.65-0.85) to 10-23 years OR 0.29 95% CI (0.22-0.38)) and with living without a partner for more than five years (ranging from 6-9 years to 10 to 23 years OR 0.80 95% CI (0.66-0.97) to 10-23 years OR 0.44 95 CI (0.37-0.52)). Those who never cohabited and experienced one or more job-losses had a particular low chance of smoking cessation (OR 0.19 95% CI (0.12-0.30). Conclusion: Number of job-losses and of broken partnerships were both inversely associated with probability of smoking cessation.
INTRODUCTION
Smoking is recognized as one of the most important causes of morbidity and premature mortality in industrialised countries. [1;2] Smoking cessation has an important impact in improving health. [3] Most smokers start in their teenage years [4] and while the majority of those who start continue to smoke throughout their adult lives, [5] some smokers quit spontaneously. Socioeconomic
However, in the same study, getting, or remaining married was associated with higher chances of smoking cessation in men compared to those who remain single in men. In a panel study by Nystedt [15] getting divorced was associated with lower chances of smoking cessation.
In life-course epidemiology the accumulation hypothesis states that the risk of poor health outcomes increases with the number of risk factors or duration of the exposure. This hypothesis has been tested related to cardiovascular disease, for which smoking is a major risk factor. To our knowledge, no studies have related accumulation of specific stressful life-events to smoking behaviours. In this study we examined the influence of history of unemployment and cohabitation over 22 years on smoking cessation. The aim of our study was to investigate the association between the history of unemployment and cohabitation and smoking cessation in mid-life and to assess whether any association depends on the number of events or the duration of an unfavourable situation. Additionally, we set out to study how the joint exposure to history of unemployment and cohabitation is related to the probability of smoking cessation.
METHODS
This study is based on a subpopulation of the metropolit project, which comprises all 12,270 boys born within the metropolitan area of Copenhagen in 1953. In 1968, the Danish Civil Registration System (CRS) was established, and each Danish resident was registered with a personal
identification number (PIN): The 11,532 members of the original metropolit population who survived until 1968 were given identification numbers by the authorities. Data from birth certificates were gathered in 1965. In 2004 the members of the cohort who were still alive and living in Denmark were sent a questionnaire about health behaviours social networks etc. Of the 9,507 eligible cohort members 6,292 (66.2 %) responded. Furthermore, the cohort was linked to registers with socioeconomic information in Statistics Denmark 1980-2003 using the PIN as a key and also with the Central Psychiatric Register and, the Central Hospital Register. We included only those from the 2004 survey participants who in addition to answering the questionnaire had a full record of register-data for the years 1980-2003 (N=6,232).
Outcome variables
smoking was more pronounced in groups in which smoking was stigmatized such as pregnant women and heart patients. The present study was based on middle-aged men from the general population and we do not judge that under-reporting is particularly pronounced in this group. The response to the question “Do you smoke?” was used to divide the participants into 3 groups: 1) current smokers (smoke on a daily basis and smoke but not every day) 2) ex-smokers 3) never smokers. The analyses of factors associated with smoking cessation were based on comparisons between ex- and current smokers, omitting the last category.
Assessment of history of cohabitation and labour-market participation
Information on history of unemployment and cohabitation was based on annual records from Statistics Denmark for the period 1980 to 2003 when cohort members were between 28 and 49 years old. Hence, it is possible to study the change of labour-market attainment as well as cohabitation status from one calendar-year to the next. Based on this information we constructed four exposure variables: number of job-losses, years unemployed, number of broken partnerships and years living without a partner.
Job-loss was defined as a change in individual labour-market participation that involved a
period of unemployment and was categorized as follows: no losses (ref), one loss, two job-losses, three or more job-losses. Job-loss status was assigned to the categories based on change of employer’s identification code. We restricted the category of job-loss to men who had been unemployed for at least three months of the calendar-year in order to exclude those who changed job with short or no intervening period of unemployment. Men with no job-losses were classified as continuously employed. Few (n=18) in the cohort were permanently outside the labour-market during the entire period and this group was pooled with the reference group i.e. those with no job-losses. [19] Years unemployed was based on information from Statistics Denmark about labour-market status for each calendar-year, which was determined by the main source of income for that year. The group of unemployed comprises both individuals who were unemployed the entire calendar-year and those who had short spells of employment, but were mainly unemployed. We grouped the men as either working (employed or self employed) or not working (due to
unemployment or for health reasons). Years unemployed was the sum of years in the non-working group between the ages of 28 and 49. This information was classified into four groups: no
In this study, men living within either marriages (heterosexual and homosexual (allowed since 1989)) or consensual unions (heterosexual only) were grouped. Two individuals living at the same address were classified as a consensual union if they had common children or were of opposite sex, and both were at least 16 years old, and the age-difference was less than 15 years, and they were not related, and there were no other adults in the household. The partner’s identification-number enabled to follow changes from one partner to another. We divided the cohort members into five groups according to their history of cohabitation between 1980 and 2003: 1) consistently cohabiting with the same partner (ref), 2) never cohabited, not living with a partner at any time during this period, 3) one broken partnership, 4) two broken partnerships, 5) three or more broken partnerships. We maintained the “never cohabited” as a separate group because of its size (n=314) and because other studies of this cohort [20] and of other populations [21] have indicated high mortality in this group. A broken partnership was defined as the end of cohabitation. The classification comprises individuals who were formerly cohabiting but during any year were living without a partner or with a new partner. Very few of the married men became widowers (n=40) during follow-up and these cases were classified as broken partnerships. [19] Years living without a
partner was based on information from Statistics Denmark about cohabiting partners for each
calendar-year assessed as described above.The sum of years in the ages 28-49 years the individual lived without a partner was classified in four groups (always living with a partner (ref), 1 to 5 years, 6 to 9 years and above 9 years).
Assessment of covariates
In this study we included information about psychiatric admissions that occurred before the measurement of job-losses and broken partnerships as confounders, while later admissions, which might be a consequence of these events, were not included. Information about admission to a
psychiatric ward was obtained from the Central Psychiatric Register for the period 1968 to 1981,
when the cohort members were 15 to 28 years old. We coded the admissions as either no admissions or at least one admission. From the social registers from 1980, we used ’educational
attainment coded into ‘high’ (at least secondary education) and ‘low’ (primary education only). Age at smoking initiation has been related to later “smoking career”. [22] Those who start to smoke
early may experience poor health at a young age which might influence their labour-market
reported in the questionnaire from 2004 and used different cut-points between the ages of 11 and 16 and found that the younger at smoking initiation the less likelihood of quitting smoking. However, the choice of cut-point did not change the association between exposures and smoking cessation. In the final analyses, we used 13 years as the cut-point. This corresponds to 22 % of the
cohort-members. We included the amount of tobacco smoked (currently for current smokers and in the past for ex-smokers) from self-reported accounts of numbers of cigarettes, pipes, cigarillos, and cigars per day and calculated the amount of tobacco per day in grams.
Statistical methods
We used logistic regression to analyse the associations between smoking cessation and history of cohabitation and job-losses. The analyses were based on men who had smoked at some time (n=4,665), i.e. leaving out never smokers. We analysed the four exposure variables (number of
job-losses, number of broken partnerships,length of periods of unemployment living without a partner)
in a series of separate models (one to five) where the covariates were included one at the time. In a sixth model we adjusted number of job-losses for number of broken partnerships and years without
employment for years living without a partner.
The score test in ‘proc logistic’ was used to test for trend (Cochran Armitage test) in models with exposure-variables included as continuous variables. Statistical interaction was tested by adding an interaction term to the models. However, the separate and joint effects were showed as by two new composite variables 1) the categories of job-loss were grouped as none versus any; and the categories of broken partnerships were grouped as none, never cohabited, and at least one broken partnership. The variables for job-losses and broken partnerships were combined leaving six combinations, the doubly-unexposed group being used as reference group. 2) time unemployed and time living without a partner was combined as unexposed to both, exposed to unemployment (1 or more years), exposed to living alone (1 or more years) and exposed to both. SAS (ver. 9,1) was used for all analysis.
RESULTS
Table 1: Distribution (in number and %) of history of job-losses and history of cohabitation (age 28-50 years), educational attainment and psychiatric admission in relation to smoking in men aged 51
History of job-losses/unemployment (1980-2003) Current smoker 2646 Ex smoker 2019 Never smoker 1567 No job-losses 1672 (63.2%) 1586 (78.6%) 1297 (82.8 %) 1 job-loss 547 (20.7%) 278 (13.8 %) 178 (11.4 %) 2 job-losses 250 (9.5%) 93 (4.6 %) 52 (3.3 %) 3+ job-losses 177 (6.7%) 62 (3.1 %) 40 (2.6 %) Time unemployed 1162 (43.9%) 1169 (57.9 %) 1038 (66.2 %) 1-5 years 924 (34.9%) 673 (33.3 %) 445 (28.4 %) 6-9 years 228 (8.6%) 88 (4.4 %) 49 (3.1 %) 10-23 years 332 (12.6%) 89 (4.4 %) 35 (2.2 %) Continuously cohabited (1980-2003) 947 (35.8%) 970 (48.0 %) 752 (48.0 %) Never cohabited 1980-2003 202 (7.6%) 69 (3.4 %) 103 (6.6 %) 1 Broken partnership 790 (29.3%) 599 (29.7 %) 435 (27.8 %) 2 Broken partnership 426 (13.9%) 251 (12.4 %) 187 (11.9 %) 3+ Broken partnership 281 (10.6%) 130 (6.4 %) 90 (5.7 %)
Time living without a partner 697 (26.3%) 685 (33.9 %) 495 (31.6 %) 1-5 years 703 (26.6%) 672 (33.3 %) 490 (31.3 %)
6-9 years 346 (13.1%) 269 (13.3 %) 200 (12.8 %)
10-23 years 900 (34.0%) 393 (19.5 %) 382 (24.4 %)
High educational attainment 1534 (58.0%) 1395 (69.1 %) 1205 (76.9 %) Low educational attainment 1112 (42.0%) 624 (30.9 %) 362 (23.1 %)
No psychiatric admissions 2535 (95.8%) 1975( 97.8 %) 1553 (99.1 %) Psychiatric admissions 111 (4.2%) 44 (2.2 %) 14 (0.9 %)
Started smoking at 14 or older 1988 (77.7 %) 1569 (83.8 %) NA
Started smoking at 13 or younger 571 (22.3 %) 304 (16.3 %) NA
Nicotine consumption g/day mean (SD)
Table 2: The association (Odds Ratios) of history of job-losses and history of cohabitation (age 28-50 years), educational attainment and psychiatric admission with smoking cessation in men aged 51
History of unemployment and cohabitation (1980-2003)
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Number of events
No job-losses 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref)
1 Job-loss 0.53 (0.45-0.63) 0.54 (0.46-0.63) 0.54 (0.46-0.64) 0.55 (0.46-0.65) 0.54 (0.46-0.64) 0.60 (0.50-0.71) 2 Job-losses 0.41 (0.32-0.53) 0.42 (0.33-0.54) 0.44 (0.34-0.57) 0.44 (0.34-0.57) 0.44 (0.34-0.57) 0.49 (0.38-0.63) 3+Job-losses 0.38 (0.28-0.51) 0.39 (0.29-0.53) 0.41 (0.30-0.55) 0.41 (0.30-0.56) 0.41 (0.30-0.55) 0.47 (0.34-0.64) Continuously cohabited (1980-2003) 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref)
Never cohabited1980-2003 0.31 (0.23-0.42) 0.32 (0.23-0.43) 0.32 (0.23-0.43) 0.32 (0.24-0.44) 0.32 (0.23-0.43) 0.38 (0.28-0.52) 1 Broken partnership 0.73 (0.63-0.84) 0.74 (0.64-0.85) 0.73 (0.64-0.85) 0.74 (0.64-0.85) 0.73 (0.63-0.85) 0.79 (0.68-0.91) 2 Broken partnership 0.59 (0.49-0.71) 0.59 (0.49-0.71) 0.59 (0.49-0.71) 0.60 (0.50-0.72) 0.59 (0.49-0.72) 0.65 (0.54-0.79) 3+ Broken partnership 0.48 (0.38-0.61) 0.50 (0.39-0.62) 0.50 (0.40-0.63) 0.50 (0.40-0.63) 0.50 (0.39-0.63) 0.56 (0.44-0.71) Duration of exposure
Time unemployed 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref)
1-5 years 0.74 (0.65-0.85) 0.75 (0.66-0.85) 0.75 (0.66-0.86) 0.75 (0.66-0.86) 0.75 (0.65-0.85) 0.79 (0.69-0.91) 6-9 years 0.40 (0.31-0.52) 0.41 (0.32-0.54) 0.42 (0.32-0.55) 0.42 (0.32-0.55) 0.42 (0.32-0.55) 0.50 (0.38-0.66) 10-23 years 0.27 (0.21-0.35) 0.28 (0.22-0.36) 0.30 (0.23-0.38) 0.30 (0.23-0.39) 0.29 (0.22-0.38) 0.41 (0.31-0.54) Time living without a partner 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref) 1 (ref)
1-5 years 1.01 (0.86-1.17) 1.01 (0.87-1.18) 0.97 (0.83-1.14) 0.98 (0.84-1.14) 0.98 (0.84-1.14) 1.03 (0.88-1.20) 6-9 years 0.83 (0.68-1.01) 0.83 (0.68-1.01) 0.80 (0.65-0.97) 0.80 (0.65-0.97) 0.80 (0.66-0.97) 0.88 (0.72-1.08) 10-23 years 0.44 (0.38-0.52) 0.45 (0.38-0.53) 0.44 (0.37-0.52) 0.45 (0.38-0.53) 0.44 (0.37-0.52) 0.56 (0.47-0.67)
Model 1 unadjusted model
Model 2 adjusted for age at smoking initiation
Model 3 adjusted for age at smoking initiation and educational attainment
Model 4 adjusted for age at smoking initiation, educational attainment, and psychiatric admissions
Model 5 adjusted for age at smoking initiation, educational attainment, psychiatric admissions, and daily nicotine consumption
We tested statistical interaction between history of unemployment and history of cohabitation in the probability of smoking cessation in two models: interaction between job-losses and broken partnership (p=0.04) and interaction between years unemployed and years living without a partner (p=0.76). Table 3 shows the separate and joint effects. Those with combined exposure of job-loss and broken partnership have a low probability of smoking cessation compared to the reference group and to those with just one of the exposures. Moreover, the never cohabitant who experienced one or more job-losses had a five times lower probability of smoking cessation compared to the doubly-unexposed group. The combined exposure to time living without a partner and time without employment was also associated with lower probability of smoking cessation.
Table 3: Adjusted Odds Ratios (OR) and 95 % Confidence Intervals (CI) for smoking cessation in relation to combinations of history of cohabitation and job-losses (age 28-39)
No of cases OR (95 % CI) No broken partnerships, no
job-loss
707 1 (ref.)
Never cohabitant, no job-loss 83 0.43 (0.29-0.65) Broken partnership,
No job-loss
825 0.77 (0.66-0.89)
No broken partnership,+ job-loss 213 0.68 (0.53-0.86) Never cohabitant, + job-loss 113 0.19 (0.12-0.30) Broken partnership,
+ job-loss
618 0.37 (0.31-0.45)
Time unemployed and living with a partner
No years unemployed and no years living without a partner
456 1 (ref.)
No years unemployed, 1+ year living without a partner
617 0.81 (0.68-0.96)
1+ year unemployed, no years living without a partner
176 0.69 (0.55-0.88)
1+ year unemployed and 1+ year living without a partner
DISCUSSION
In this study we found consistent support for the accumulation hypothesis as both number of job-loss and broken partnerships were inversely related to smoking cessation. Furthermore, the chance of smoking cessation decreased with duration of unemployment and of living without a partner. Those with exposure to both job-losses and broken partnerships had low probability of smoking cessation; and particularly the never cohabiting with job-losses had low probability of smoking cessation.
We found no studies that investigated accumulation of the same factors related to smoking cessation. However, some studies have focused on related issues and some have linked accumulation of social risk factors to health behaviours. Nystedt [15] investigated the associations between smoking behaviour and marital life-course changes. He found that those who divorced or had never cohabited were less likely to cease smoking while this did not apply to those with multiple changes in marital status. However, multiple marital changes and divorce was associated with starting to smoke. The multiple marital changes in Nystedt´s study are not entirely comparable to the present study as they might involve multiple changes in an out of marriage as a result of divorce, remarriage and widowhood while the present study considered only cessation of
partnerships. Montgomery et al. [23] found that the risk of being a smoker increased with time spent unemployed between the ages of 16 and 33. Although these studies use different smoking
outcomes, they both agree with the present study in that the accumulation of exposures related to the labour-market is associated with smoking behaviours.
Strengths and limitations
study included only men and mainly heterosexual relationships, and it is very likely that exposures related to labour-market and family-life affect women differently. [25] Smoking status can change several times and these changes have been related to job-losses and broken partnerships in other studies. [26;27] However, smoking was measured only once in the metropolit project and we were not able to study how exposures were related to changes in smoking behaviours.
We found that the association between history of unemployment and smoking cessation differed when history of cohabitation was included and vice versa. In this study design it was not possible to determine whether they each acted as confounders or as mediators for each other as they were measured during the same time span. We found that the associations between history of unemployment and partnership and smoking were affected to a small degree by inclusion of psychiatric admissions. However, this might be due to the fact that only the more severe cases of psychiatric illness are registered in hospital records. Milder cases of mental disorders might
influence on the results, but unfortunately this information was unavailable. Further, factors such as social support, depression and nicotine dependence were either unmeasured or measured
simultaneous with the outcome. Thus, future studies with information on the temporal order of these factors could spread light on the role of these in relation to accumulated events and smoking
behaviours. Future life-course studies that include both disease outcomes and behavioural variables could focus on the question of whether the association between accumulated social risk factors and disease are mediated by health behaviours.
Acknowledgement:
The authors thank K Svalastoga, E Høgh, P Wolf, T Rishøj, G Strande-Sørensen, E Manniche, B Holten, I A Weibull and A Ortmann who established the data between 1965 and 1983.
Competing interests: All authors have nothing to declare.
Funding:
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